SURF uses teacher-student remixing within a flow-matching framework to achieve unsupervised source separation and reports new state-of-the-art results on audio and image benchmarks.
Noisy speech database for training speech enhancement algorithms and TTS models, 2016,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
READ is a reference-free ASR hypothesis scorer that measures acoustic discrepancy via conditional likelihood from a pretrained auto-regressive TTS model and yields up to 20% relative error rate reduction when used for refinement.
citing papers explorer
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SURF: Separation via Unsupervised Remixing Flow
SURF uses teacher-student remixing within a flow-matching framework to achieve unsupervised source separation and reports new state-of-the-art results on audio and image benchmarks.
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Read What You Hear: Reference-Free Hypotheses Evaluation with Acoustic Discrepancy
READ is a reference-free ASR hypothesis scorer that measures acoustic discrepancy via conditional likelihood from a pretrained auto-regressive TTS model and yields up to 20% relative error rate reduction when used for refinement.